一类分数阶微积分的中值定理及应用

Riemann-Liouville分数阶微积分算子是一类带有一个函数的分数阶微积分算子的特殊情形，以Riemann-Liouville分数阶微积分算子的积分中值定理和微分中值定理为基础，我们得到了一类带有一个函数的分数阶微积分算子的积分中值定理和微分中值定理，并给出其在计算方面的一些应用。     

磨矿动力学研究现状及应用

磨矿动力学是描述被磨物料的磨碎速率与磨矿时间之间关系规律的一种数学模型，对分析物料在磨矿过程中的粒级及能量变化具有重要作用。为充分发挥磨矿动力学在磨矿过程中的作用，论文在分析国内外研究现状的基础上，系统介绍了两种典型的磨矿动力学模型：m阶磨矿动力学模型和磨矿总体平衡动力学模型，分析了模型中各参数的含义；以磨矿总体平衡动力学模型为重点，分析了破碎速率函数和破碎分布函数的求解方式，包括零阶产出率法、奥-勒理论简算法、卡普尔G-H算法以及经验公式法等；从物料性质、磨矿介质及配比、磨矿方式及参数、化学添加剂等几个方面分析了影响磨矿动力学模型的因素；指出了磨矿动力学模型在矿物加工工程领域的应用现状并对其未来的研究方向提出展望。研究表明磨矿动力学在矿物加工领域具有广泛而重要的应用，为进一步改善磨矿工艺提供了理论依据。     

On a marching level-set method for extended discontinuous Galerkin methods for incompressible two-phase flows: Application to two-dimensional settings

In this work a solver for two-dimensional, instationary two-phase flows on the basis of the extended discontinuous Galerkin (extended DG/XDG) method is presented. The XDG method adapts the approximation space conformal to the position of the interface. This allows a subcell accurate representation of the incompressible Navier-Stokes equations in their sharp interface formulation. The interface is described as the zero set of a signed-distance level-set function and discretized by a standard DG method. For the interface, resp. level-set, evolution an extension velocity field is used and a two-staged algorithm is presented for its construction on a narrow-band. On the cut-cells a monolithic elliptic extension velocity method is adapted and a fast-marching procedure on the neighboring cells. The spatial discretization is based on a symmetric interior penalty method and for the temporal discretization a moving interface approach is adapted. A cell agglomeration technique is utilized for handling small cut-cells and topology changes during the interface motion. The method is validated against a wide range of typical two-phase surface tension driven flow phenomena in a 2D setting including capillary waves, an oscillating droplet and the rising bubble benchmark.     

基于农产品品牌社会责任的消费者智能消费推荐研究

为了在竞争日益激烈的市场中提高竞争力,达到个性化销售目的,创造更大品牌价值,提出一种基于农产品品牌社会责任的消费者智能消费推荐研究。实验利用离散函数及品牌认可度描述推荐结果,分析推荐结果指数,证明基于社会责任的智能推荐研究令消费者认可度更高,与文献方法比较推荐结果有更高的精确度,设计的推荐模型可实现农产品个性销售目的,令农产品有更大的发展空间。     

负压吸引技术应用于大面积烧伤患者围术期的效果探究

目的:探究环磷酸腺苷联合负压吸引技术应用于大面积烧伤患者围术期的效果及肾保护作用探究。方法:选择2018年12月到2020年12月于医院治疗的120例大面积烧伤患者为研究对象,以随机数字表法对患者分组,60例患者为研究组,60例患者为对照组,对照组给予负压吸引技术治疗,研究组在此基础上给予环磷酸腺苷治疗,治疗前、后测定两组患者干扰素-γ(IFN-γ)、白细胞介素-2(IL-2)、白细胞介素-10(IL-0)、白细胞介素-6(IL-6)、可溶性血管细胞粘附分子-1(sVCAM-1)、一氧化氮(NO)、内皮素(ET-1)、血管内皮生长因子(VEGF)、胱抑素C(Cys-C)、肌酐(Scr)、血尿素氮(BUN)、肾损伤分子-1(KIM-1)水平,记录两组患者手术时间、麻醉苏醒时间、住院时间。结果:研究组IFN-γ、IL-6水平低于对照组(P<0.05),研究组患者IL-2、IL-10水平高于对照组(P<0.05),研究组NO、VEGF水平高于对照组(P<0.05),研究组患者sVCAM-1、ET-1水平低于对照组(P<0.05),研究组患者Cys-C、Scr、BUN、KIM-1水平低于对照组(P<0.05),研究组手术时间低于对照组(P>0.05),研究组麻醉苏醒时间、住院时间低于对照组(P<0.05)。结论:环磷酸腺苷联合负压吸引技术应用于大面积烧伤围术期患者,可降低患者IFN-γ、IL-6水平,提升患者IL-2、IL-10水平,抑制患者炎症,改善患者血管内皮功能,降低患者Cys-C、Scr、BUN、KIM-1水平,减少患者肾功能损伤,减少患者麻醉苏醒时间及住院时间。     

Ni-hydrotalcite loading on carbon as co-catalyst for fermentative hydrogen production

The influence of Ni-hydrotalcite (HT) loading on the activity and stability of Ni-HT supported on activated carbon (Ni-HT/AC) was investigated for fermentative hydrogen production. The basic sites of Ni-HT loading on AC support significantly boosted the catalytic performance with the initial faster rate. The combined function catalyst of Ni-HT/AC facilitates the rapid decomposition of saccharides and high selectivity to fructose that attained the maximum hydrogen production within 24 h. The optimum dose of Ni-HT/AC at 8.33 g/L showed a 25.84% increment over the control. In addition, shortening the lagging phase time at 1.50 h was achieved. The high adsorption capacity of lactic acid was induced with the basic sites of Ni-HT/AC. However, a deactivation of the Ni-HT/AC during prolonged fermentation was associated with metabolites formation, causing the leaching of Mg²⁺ ions from the surface of AC supported Ni-HT and reducing surface basicity of Ni-HT/AC.     

Design of data feature-driven 1D/2D convolutional neural networks classifier for recycling black plastic wastes through laser spectroscopy

In this study, two types of convolutional neural network (CNN) classifiers are designed to handle the problem of classifying black plastic wastes. In particular, the black plastic wastes have the property of absorbing laser light coming from spectrometer. Therefore, the classification of black plastic wastes remains still a challenging problem compared to classifying other colored plastic wastes using existing spectroscopy (i.e., NIR). When it comes the classification problem of black plastic wastes, effective classification techniques by the laser spectroscopy of Fourier Transform-Infrared Radiation (FT-IR) with Attenuated Total Reflectance (ATR) and Raman to analyze the classification problem of black plastic wastes are introduced. Due to the strong ability of extracting spatial features and remarkable performance in image classification, 1D and 2D CNN through data features are designed as classifiers. The technique of chemical peak points selection is considered to reduce data redundancy. Furthermore, through the selection of data features based on the extracted 1D data with peak points is introduced. Experimental results demonstrate that 2DCNN classifier designed with the help of 2D data feature selection as well as 1DCNN classifier shows the best performance compared with other reported methods for classifying black plastic wastes.     

一种无线传感器网络中的信息驱动节点选择机制

提出了一种信息驱动的节点选择机制,应用于无线传感器网络中的目标估值。其方法是,以传感器节点的测量值与目标状态的估计分布之间的互信息作为信息效用函数,度量节点的测量值对目标状态估计的信息贡献,选择信息贡献值大的节点参与卡尔曼滤波过程进行迭代;应用基于地理位置信息的路由算法顺序访问选中的节点,并建立与Sink节点之间的路由,路径上的节点依次进行卡尔曼迭代以修正估计的状态值。仿真结果表明,该机制涉及的节点数目较少,总的通信距离较短,但目标估值的性能很好。